Why make dashboards with Shiny?

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Shiny apps contained within RMarkdown presentations are useful for exploring small, individual datasets and where the codebase is small. Split-file Shiny apps are useful for creating large-scale interfaces through which large datasets can be explored by others through interactive visualisations, which are often called dashboards. Split-file apps are also more useful for large code base that would be difficult to work with within a single RMarkdown file. This video tutorial covers the benefits of building split-file apps or dashboards, including the ability to directly embed these within your RMarkdown presentations.

- [Voiceover] Why Make Dashboards with Shiny?…Well there's three very good reasons…R is a programming language…with an ecosystem built for data analysis.…Modeling, machine learning, and data science in general.…Shiny allows you to incredibly easily convert…these script files into interactive applications.…By integrating your analytical scripts…directly into the dashboard workflow…you're ensuring your dashboards…are always up to date, and that your…data experts don't depend on different…tools for analysis and communication of results.…

Multi-page responsive dashboards…can easily be built in Shiny…and natively supports the Bootstrap framework.…Including responsive twelve column layouts.…Finally, Shiny apps can easily be…embedded anywhere for the use of iPhones.…If your Shiny app is hosted on a Shiny server…or a Shinyapps.io service, and of course…Shiny apps can be easily embedded…into your R markdown presentations.…In addition to these great points…it's amazing how few R users know about html widgets…a collection of incredible libraries…

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Released

4/29/2016

Analyzing big data is great, but not if you can't share your results. In this course, Martin Hadley shows how to create interactive presentations of large data sets with R, RStudio, and Shiny, an R-based tool for producing interactive, web-ready data visualizations. Learn why these tools are important to data scientists, how to configure and install them, and how to use them to make your findings more clear and engaging.

Discover the different types of presentations you can make right out of the box with R Markdown templates (built right into RStudio) and how to customize the templates with CSS. Find out how to register for RPubs to deploy RStudio presentations for sharing, and then go beyond the basics with Shiny—adding interactivity and creating embeddable dashboards without the need for HTML or JavaScript.

This is an exciting course for analysts who want to increase the relevance and visibility of their work. Make sure to watch the knowledge checks at the end of each chapter to test your new skills.